Modelling and simulating in systems biology: an approach based on multi-agent systems

Systems Biology is an innovative way of doing biology recently raised in bio-informatics contexts, characterised by the study of biological systems as complex systems with a strong focus on the system level and on the interaction dimension. In other words, the objective is to understand biological systems as a whole, putting on the foreground not only the study of the individual parts as standalone parts, but also of their interaction and of the global properties that emerge at the system level by means of the interaction among the parts. This thesis focuses on the adoption of multi-agent systems (MAS) as a suitable paradigm for Systems Biology, for developing models and simulation of complex biological systems. Multi-agent system have been recently introduced in informatics context as a suitabe paradigm for modelling and engineering complex systems. Roughly speaking, a MAS can be conceived as a set of autonomous and interacting entities, called agents, situated in some kind of nvironment, where they fruitfully interact and coordinate so as to obtain a coherent global system behaviour. The claim of this work is that the general properties of MAS make them an effective approach for modelling and building simulations of complex biological systems, following the methodological principles identified by Systems Biology. In particular, the thesis focuses on cell populations as biological systems. In order to support the claim, the thesis introduces and describes (i) a MAS-based model conceived for modelling the dynamics of systems of cells interacting inside cell environment called niches. (ii) a computational tool, developed for implementing the models and executing the simulations. The tool is meant to work as a kind of virtual laboratory, on top of which kinds of virtual experiments can be performed, characterised by the definition and execution of specific models implemented as MASs, so as to support the validation, falsification and improvement of the models through the observation and analysis of the simulations. A hematopoietic stem cell system is taken as reference case study for formulating a specific model and executing virtual experiments.

Integrazione di algoritmi di visione basati su flusso ottico per il controllo di un velivolo senza pilota

Il lavoro svolto in questa tesi si colloca nell’area della robotica aerea e della visione artificiale attraverso l’integrazione di algoritmi di visione per il controllo di un velivolo senza pilota. Questo lavoro intende dare un contributo al progetto europeo SHERPA (Smart collaboration between Humans and ground-aErial Robots for imProving rescuing activities in Alpine environments), coordinato dall’università di Bologna e con la compartecipazione delle università di Brema, Zurigo, Twente, Leuven, Linkopings, del CREATE (Consorzio di Ricerca per l’Energia e le Applicazioni Tecnologiche dell’Elettromagnetismo), di alcune piccole e medie imprese e del club alpino italiano, che consiste nel realizzare un team di robots eterogenei in grado di collaborare con l’uomo per soccorrere i dispersi nell’ambiente alpino. L’obiettivo di SHERPA consiste nel progettare e integrare l’autopilota all’interno del team. In tale contesto andranno gestiti problemi di grande complessità, come il controllo della stabilità del velivolo a fronte di incertezze dovute alla presenza di vento, l’individuazione di ostacoli presenti nella traiettoria di volo, la gestione del volo in prossimità di ostacoli, ecc. Inoltre tutte queste operazioni devono essere svolte in tempo reale. La tesi è stata svolta presso il CASY (Center for Research on Complex Automated Systems) dell’università di Bologna, utilizzando per le prove sperimentali una PX4FLOW Smart Camera. Inizialmente è stato studiato un autopilota, il PIXHAWK, sul quale è possibile interfacciare la PX4FLOW, in seguito sono stati studiati e simulati in MATLAB alcuni algoritmi di visione basati su flusso ottico. Infine è stata studiata la PX4FLOW Smart Camera, con la quale sono state svolte le prove sperimentali. La PX4FLOW viene utilizzata come interfaccia alla PIXHAWK, in modo da eseguire il controllo del velivolo con la massima efficienza. E’ composta da una telecamera per la ripresa della scena, un giroscopio per la misura della velocità angolare, e da un sonar per le misure di distanza. E’ in grado di fornire la velocità di traslazione del velivolo, e quest’ultima, integrata, consente di ricostruire la traiettoria percorsa dal velivolo.

Teoria del consenso e applicazione al problema del coordinamento del moto di robot.

Il sempre crescente numero di applicazioni di reti di sensori, robot cooperanti e formazioni di veicoli, ha fatto sì che le problematiche legate al coordinamento di sistemi multi-agente (MAS) diventassero tra le più studiate nell’ambito della teoria dei controlli. Esistono numerosi approcci per affrontare il problema, spesso profondamente diversi tra loro. La strategia studiata in questa tesi è basata sulla Teoria del Consenso, che ha una natura distribuita e completamente leader-less; inoltre il contenuto informativo scambiato tra gli agenti è ridotto al minimo. I primi 3 capitoli introducono ed analizzano le leggi di interazione (Protocolli di Consenso) che permettono di coordinare un Network di sistemi dinamici. Nel capitolo 4 si pensa all'applicazione della teoria al problema del "loitering" circolare di più robot volanti attorno ad un obiettivo in movimento. Si sviluppa a tale scopo una simulazione in ambiente Matlab/Simulink, che genera le traiettorie di riferimento di raggio e centro impostabili, a partire da qualunque posizione iniziale degli agenti. Tale simulazione è stata utilizzata presso il “Center for Research on Complex Automated Systems” (CASY-DEI Università di Bologna) per implementare il loitering di una rete di quadrirotori "CrazyFlie". I risultati ed il setup di laboratorio sono riportati nel capitolo 5. Sviluppi futuri si concentreranno su algoritmi locali che permettano agli agenti di evitare collisioni durante i transitori: il controllo di collision-avoidance dovrà essere completamente indipendente da quello di consenso, per non snaturare il protocollo di Consenso stesso.

Analysis of Lead-Acid batteries with a third-order dynamical model

Electrical energy storage is a really important issue nowadays. As electricity is not easy to be directly stored, it can be stored in other forms and converted back to electricity when needed. As a consequence, storage technologies for electricity can be classified by the form of storage, and in particular we focus on electrochemical energy storage systems, better known as electrochemical batteries. Largely the more widespread batteries are the Lead-Acid ones, in the two main types known as flooded and valve-regulated. Batteries need to be present in many important applications such as in renewable energy systems and in motor vehicles. Consequently, in order to simulate these complex electrical systems, reliable battery models are needed. Although there exist some models developed by experts of chemistry, they are too complex and not expressed in terms of electrical networks. Thus, they are not convenient for a practical use by electrical engineers, who need to interface these models with other electrical systems models, usually described by means of electrical circuits. There are many techniques available in literature by which a battery can be modeled. Starting from the Thevenin based electrical model, it can be adapted to be more reliable for Lead-Acid battery type, with the addition of a parasitic reaction branch and a parallel network. The third-order formulation of this model can be chosen, being a trustworthy general-purpose model, characterized by a good ratio between accuracy and complexity. Considering the equivalent circuit network, all the useful equations describing the battery model are discussed, and then implemented one by one in Matlab/Simulink. The model has been finally validated, and then used to simulate the battery behaviour in different typical conditions.

Extending the 2P-Kt ecosystem: CLP and Labelled LP

The ability to create hybrid systems that blend different paradigms has now become a requirement for complex AI systems usually made of more than a component. In this way, it is possible to exploit the advantages of each paradigm and exploit the potential of different approaches such as symbolic and non-symbolic approaches. In particular, symbolic approaches are often exploited for their efficiency, effectiveness and ability to manage large amounts of data, while symbolic approaches are exploited to ensure aspects related to explainability, fairness, and trustworthiness in general. The thesis lies in this context, in particular in the design and development of symbolic technologies that can be easily integrated and interoperable with other AI technologies. 2P-Kt is a symbolic ecosystem developed for this purpose, it provides a logic-programming (LP) engine which can be easily extended and customized to deal with specific needs. The aim of this thesis is to extend 2P-Kt to support constraint logic programming (CLP) as one of the main paradigms for solving highly combinatorial problems given a declarative problem description and a general constraint-propagation engine. A real case study concerning school timetabling is described to show a practical usage of the CLP(FD) library implemented. Since CLP represents only a particular scenario for extending LP to domain-specific scenarios, in this thesis we present also a more general framework: Labelled Prolog, extending LP with labelled terms and in particular labelled variables. The designed framework shows how it is possible to frame all variations and extensions of LP under a single language reducing the huge amount of existing languages and libraries and focusing more on how to manage different domain needs using labels which can be associated with every kind of term. Mapping of CLP into Labeled Prolog is also discussed as well as the benefits of the provided approach.